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» Approximation Methods for Supervised Learning
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AAAI
2007
13 years 9 months ago
Learning Language Semantics from Ambiguous Supervision
This paper presents a method for learning a semantic parser from ambiguous supervision. Training data consists of natural language sentences annotated with multiple potential mean...
Rohit J. Kate, Raymond J. Mooney

Publication
222views
14 years 4 months ago
Algorithms and Bounds for Rollout Sampling Approximate Policy Iteration
Abstract: Several approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a supervis...
Christos Dimitrakakis, Michail G. Lagoudakis
NIPS
2004
13 years 8 months ago
A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning
We consider the situation in semi-supervised learning, where the "label sampling" mechanism stochastically depends on the true response (as well as potentially on the fe...
Saharon Rosset, Ji Zhu, Hui Zou, Trevor Hastie
ICRA
2007
IEEE
126views Robotics» more  ICRA 2007»
14 years 1 months ago
Learning slip behavior using automatic mechanical supervision
— We address the problem of learning terrain traversability properties from visual input, using automatic mechanical supervision collected from sensors onboard an autonomous vehi...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
EUSFLAT
2009
140views Fuzzy Logic» more  EUSFLAT 2009»
13 years 5 months ago
Incremental Possibilistic Approach for Online Clustering and Classification
In this paper, we propose to develop the supervised classification method Fuzzy Pattern Matching to be in addition a non supervised one. The goal is to monitor dynamic systems with...
Moamar Sayed Mouchaweh, Bernard Riera